{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from palettable.colorbrewer.diverging import RdBu_11\n",
    "from palettable.colorbrewer.sequential import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get data sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<defs>\n",
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       "<title>Show/Hide data repr</title>\n",
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       "<title>Show/Hide attributes</title>\n",
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       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
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       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
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       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
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       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
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       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
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       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
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       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-item input:enabled + label {\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
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       "\n",
       ".xr-section-summary {\n",
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       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
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       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-summary-in + label:before {\n",
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       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
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       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
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       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
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       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
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       "\n",
       ".xr-dim-list:after {\n",
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       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
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       "\n",
       ".xr-var-list,\n",
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       "  display: contents;\n",
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       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
       ".xr-var-name {\n",
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       "\n",
       ".xr-var-dims {\n",
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       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
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       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
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       ".xr-preview,\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
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       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6bc3ab0e-f125-4d1e-9be6-06643ff1758b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6bc3ab0e-f125-4d1e-9be6-06643ff1758b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>easting</span>: 56</li><li><span class='xr-has-index'>northing</span>: 36</li><li><span class='xr-has-index'>time</span>: 8783</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1b137da2-b06d-41f7-be8f-91330c51c651' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b137da2-b06d-41f7-be8f-91330c51c651' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1980-01-01T01:00:00 ... 1980-12-31T23:00:00</div><input id='attrs-666f475c-5960-4fc9-8a77-753167ed2e3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-666f475c-5960-4fc9-8a77-753167ed2e3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb70aa54-2f9d-4565-9c25-bd37e93f7b8c' class='xr-var-data-in' type='checkbox'><label for='data-eb70aa54-2f9d-4565-9c25-bd37e93f7b8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><pre class='xr-var-data'>array([&#x27;1980-01-01T01:00:00.000000000&#x27;, &#x27;1980-01-01T02:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-01T03:00:00.000000000&#x27;, ..., &#x27;1980-12-31T21:00:00.000000000&#x27;,\n",
       "       &#x27;1980-12-31T22:00:00.000000000&#x27;, &#x27;1980-12-31T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>northing</span></div><div class='xr-var-dims'>(northing)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-110000.0 -107000.0 ... -5000.0</div><input id='attrs-1996c1ee-d078-4052-92ae-b45042bf1231' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1996c1ee-d078-4052-92ae-b45042bf1231' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a0e7e1b-c837-480b-b7c5-8266d71b6bd3' class='xr-var-data-in' type='checkbox'><label for='data-5a0e7e1b-c837-480b-b7c5-8266d71b6bd3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><pre class='xr-var-data'>array([-110000., -107000., -104000., -101000.,  -98000.,  -95000.,  -92000.,\n",
       "        -89000.,  -86000.,  -83000.,  -80000.,  -77000.,  -74000.,  -71000.,\n",
       "        -68000.,  -65000.,  -62000.,  -59000.,  -56000.,  -53000.,  -50000.,\n",
       "        -47000.,  -44000.,  -41000.,  -38000.,  -35000.,  -32000.,  -29000.,\n",
       "        -26000.,  -23000.,  -20000.,  -17000.,  -14000.,  -11000.,   -8000.,\n",
       "         -5000.], dtype=float32)</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>easting</span></div><div class='xr-var-dims'>(easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1542000.0 ... -1377000.0</div><input id='attrs-06656f2c-2442-4691-b168-e2f9edecc84f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06656f2c-2442-4691-b168-e2f9edecc84f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ab71a29-8457-411b-9549-ce1b8b2261bb' class='xr-var-data-in' type='checkbox'><label for='data-6ab71a29-8457-411b-9549-ce1b8b2261bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><pre class='xr-var-data'>array([-1542000., -1539000., -1536000., -1533000., -1530000., -1527000.,\n",
       "       -1524000., -1521000., -1518000., -1515000., -1512000., -1509000.,\n",
       "       -1506000., -1503000., -1500000., -1497000., -1494000., -1491000.,\n",
       "       -1488000., -1485000., -1482000., -1479000., -1476000., -1473000.,\n",
       "       -1470000., -1467000., -1464000., -1461000., -1458000., -1455000.,\n",
       "       -1452000., -1449000., -1446000., -1443000., -1440000., -1437000.,\n",
       "       -1434000., -1431000., -1428000., -1425000., -1422000., -1419000.,\n",
       "       -1416000., -1413000., -1410000., -1407000., -1404000., -1401000.,\n",
       "       -1398000., -1395000., -1392000., -1389000., -1386000., -1383000.,\n",
       "       -1380000., -1377000.], dtype=float32)</pre></li></ul></div></li><li class='xr-section-item'><input id='section-6a1f6d95-f0ba-4b6b-91ca-196576e16ffc' class='xr-section-summary-in' type='checkbox'  ><label for='section-6a1f6d95-f0ba-4b6b-91ca-196576e16ffc' class='xr-section-summary' >Data variables: <span>(22)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>dw</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4d23ec59-13f6-46dc-9fd8-0f6d9048fd6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d23ec59-13f6-46dc-9fd8-0f6d9048fd6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b259420c-1b0f-42d9-ab28-e0d6f445da0e' class='xr-var-data-in' type='checkbox'><label for='data-b259420c-1b0f-42d9-ab28-e0d6f445da0e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>wind_from_direction</dd><dt><span>units :</span></dt><dd>degree</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>ERODEDMASS</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-56034a56-5018-4eb7-86a9-4a7eae95210b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56034a56-5018-4eb7-86a9-4a7eae95210b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a9bb027-7ed7-4a49-96ae-ee7e3eabc964' class='xr-var-data-in' type='checkbox'><label for='data-3a9bb027-7ed7-4a49-96ae-ee7e3eabc964' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>ET</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-42eb21e3-8a84-4314-b087-8b487a3b7f6a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-42eb21e3-8a84-4314-b087-8b487a3b7f6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ec92a1f-5813-4c37-8507-f04333c7df61' class='xr-var-data-in' type='checkbox'><label for='data-3ec92a1f-5813-4c37-8507-f04333c7df61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>snd</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-51033de2-1f4a-46be-a75e-f4606747eca6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51033de2-1f4a-46be-a75e-f4606747eca6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e299836-e638-4863-baac-2e8b00c806e3' class='xr-var-data-in' type='checkbox'><label for='data-3e299836-e638-4863-baac-2e8b00c806e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_snow_thickness</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>rlds</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0a90b355-c1d6-4ac8-bc55-a24602c34494' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a90b355-c1d6-4ac8-bc55-a24602c34494' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e34e625-8962-4ddf-96b0-064fd514bc53' class='xr-var-data-in' type='checkbox'><label for='data-4e34e625-8962-4ddf-96b0-064fd514bc53' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_downwelling_longwave_flux_in_air</dd><dt><span>units :</span></dt><dd>W/m2</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>rsds</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f4d5a87f-7575-4c43-bd82-984cdea5a232' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4d5a87f-7575-4c43-bd82-984cdea5a232' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bad599da-a1a8-42ea-a0b6-c518aab8699a' class='xr-var-data-in' type='checkbox'><label for='data-bad599da-a1a8-42ea-a0b6-c518aab8699a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_downwelling_shortwave_flux_in_air</dd><dt><span>units :</span></dt><dd>W/m2</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>MS_HNW</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4a0ff910-4cf2-44c8-9ffe-622e47a40328' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a0ff910-4cf2-44c8-9ffe-622e47a40328' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ea92e5e-5b53-4e98-accd-a19a081a7310' class='xr-var-data-in' type='checkbox'><label for='data-8ea92e5e-5b53-4e98-accd-a19a081a7310' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>MS_SNOWPACK_RUNOFF</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-67243a94-7b1c-4fdc-b3f9-96fe5abf73f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67243a94-7b1c-4fdc-b3f9-96fe5abf73f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfab6636-cec3-4b88-ba91-786765a4d642' class='xr-var-data-in' type='checkbox'><label for='data-bfab6636-cec3-4b88-ba91-786765a4d642' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>Snowpack_runoff</dd><dt><span>long_name :</span></dt><dd>Runoff at bottom of snowpack (positive = downward flux)</dd><dt><span>units :</span></dt><dd>kg/m2</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>MS_WIND</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-46e37c81-86ca-457e-9d22-fe679963e300' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46e37c81-86ca-457e-9d22-fe679963e300' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4e5f543-9f92-4af0-895a-8447d35f4e48' class='xr-var-data-in' type='checkbox'><label for='data-d4e5f543-9f92-4af0-895a-8447d35f4e48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1fd5c3a1-b6f4-44c3-b8f9-f435c3806b99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1fd5c3a1-b6f4-44c3-b8f9-f435c3806b99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fbc236f-4931-4d7d-b301-274fa8379ab1' class='xr-var-data-in' type='checkbox'><label for='data-9fbc236f-4931-4d7d-b301-274fa8379ab1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>units :</span></dt><dd>kg/m2/s</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>hur</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6be44a70-320b-43e3-b5f4-75a2eb0badf4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6be44a70-320b-43e3-b5f4-75a2eb0badf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3efc8d30-1d0d-4c1a-a0ec-4116d00f3a75' class='xr-var-data-in' type='checkbox'><label for='data-3efc8d30-1d0d-4c1a-a0ec-4116d00f3a75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>snow_density</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8f475422-32c4-47ae-b98c-93d1ed3db944' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f475422-32c4-47ae-b98c-93d1ed3db944' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e723ac79-88ff-4b61-ac8a-bf392977895e' class='xr-var-data-in' type='checkbox'><label for='data-e723ac79-88ff-4b61-ac8a-bf392977895e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>snow_density</dd><dt><span>units :</span></dt><dd>kg/m3</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>SFC_SUBL</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-eef48282-56ba-4e52-9362-f4ca7e03fbba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eef48282-56ba-4e52-9362-f4ca7e03fbba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06bb4e1f-6999-4900-ae73-318faec149c3' class='xr-var-data-in' type='checkbox'><label for='data-06bb4e1f-6999-4900-ae73-318faec149c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>Surface_evaporation_sublimation</dd><dt><span>long_name :</span></dt><dd>Evaporation and sublimated mass from surface (positive = downward flux)</dd><dt><span>units :</span></dt><dd>kg/m2</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>SURF_ALB</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b1d6d316-c0da-4493-9e4a-afde684cdadc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b1d6d316-c0da-4493-9e4a-afde684cdadc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d79346e9-bf48-4041-9860-2be45f9cd132' class='xr-var-data-in' type='checkbox'><label for='data-d79346e9-bf48-4041-9860-2be45f9cd132' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>swe</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9bab1df0-5c79-4b7b-a9d3-b9f8b66eef58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bab1df0-5c79-4b7b-a9d3-b9f8b66eef58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-559898c4-5b0e-4884-8674-cf31cd9f32ef' class='xr-var-data-in' type='checkbox'><label for='data-559898c4-5b0e-4884-8674-cf31cd9f32ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>lwe_thickness_of_surface_snow_amount</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>ta</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8a674179-6f93-4fc0-ac34-649b21f6a785' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a674179-6f93-4fc0-ac34-649b21f6a785' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dc4d327-f8a7-4c2e-a968-28cb63388e02' class='xr-var-data-in' type='checkbox'><label for='data-7dc4d327-f8a7-4c2e-a968-28cb63388e02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>near surface air temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>TOP_ALB</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2e529438-b34f-46d3-9229-eabd6e593613' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2e529438-b34f-46d3-9229-eabd6e593613' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8ab371a-79d1-4007-af3d-f976b8d57216' class='xr-var-data-in' type='checkbox'><label for='data-c8ab371a-79d1-4007-af3d-f976b8d57216' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>TSG</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-09586ecd-0611-4621-bd21-e1b84223c5f6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-09586ecd-0611-4621-bd21-e1b84223c5f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f0f808c-0ca4-4d54-9927-cd8f0da6d418' class='xr-var-data-in' type='checkbox'><label for='data-6f0f808c-0ca4-4d54-9927-cd8f0da6d418' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>ts</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-57750d1b-bb6a-4df0-b009-365917b32903' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57750d1b-bb6a-4df0-b009-365917b32903' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-449d3d99-1ebd-4597-8289-8c417318db65' class='xr-var-data-in' type='checkbox'><label for='data-449d3d99-1ebd-4597-8289-8c417318db65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>ws</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e13f5fe8-c2c1-4893-939b-e861f19322d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e13f5fe8-c2c1-4893-939b-e861f19322d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-002993b7-9e30-4930-8699-ada6cdb71679' class='xr-var-data-in' type='checkbox'><label for='data-002993b7-9e30-4930-8699-ada6cdb71679' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>wind_speed</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>VW_DRIFT</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ad625f59-2bd7-489d-8b4b-560e6d91d742' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ad625f59-2bd7-489d-8b4b-560e6d91d742' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d53817f5-576d-4388-9441-6b068532f157' class='xr-var-data-in' type='checkbox'><label for='data-d53817f5-576d-4388-9441-6b068532f157' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>WINDEROSIONDEPOSITION</span></div><div class='xr-var-dims'>(time, northing, easting)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-29a28ea2-47da-4cae-ad35-b0e636488c61' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-29a28ea2-47da-4cae-ad35-b0e636488c61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c9bc852-ccb8-4baf-9d8e-2b6c0abf2964' class='xr-var-data-in' type='checkbox'><label for='data-5c9bc852-ccb8-4baf-9d8e-2b6c0abf2964' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[17706528 values with dtype=float32]</pre></li></ul></div></li><li class='xr-section-item'><input id='section-4ba0b70f-d1d1-4227-802a-bcb0c5067e33' class='xr-section-summary-in' type='checkbox'  ><label for='section-4ba0b70f-d1d1-4227-802a-bcb0c5067e33' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>date_created :</span></dt><dd>2020-10-29</dd><dt><span>creator_name :</span></dt><dd>erke2265</dd><dt><span>source :</span></dt><dd>MeteoIO-2.90</dd><dt><span>history :</span></dt><dd>2020-10-29T15:08:14Z, erke2265@shas0144.rc.int.colorado.edu, MeteoIO-2.90</dd><dt><span>keywords_vocabulary :</span></dt><dd>AGU Index Terms</dd><dt><span>keywords :</span></dt><dd>Cryosphere, Mass Balance, Energy Balance, Atmosphere, Land/atmosphere interactions, Climatology</dd><dt><span>title :</span></dt><dd>Gridded data for various parameters and timesteps</dd><dt><span>institution :</span></dt><dd>colorado.edu</dd><dt><span>product_version :</span></dt><dd>1.0</dd><dt><span>Conventions :</span></dt><dd>CF-1.6,ACDD-1.3</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF-1.6</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>EPSG:3031</dd><dt><span>geospatial_bounds :</span></dt><dd>Polygon ((-1557000.0000000000 -125000.0000000000, -1359000.0000000000 -125000.0000000000, -1359000.0000000000 13000.0000000000, -1557000.0000000000 13000.0000000000))</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                (easting: 56, northing: 36, time: 8783)\n",
       "Coordinates:\n",
       "  * time                   (time) datetime64[ns] 1980-01-01T01:00:00 ... 1980-12-31T23:00:00\n",
       "  * northing               (northing) float32 -110000.0 -107000.0 ... -5000.0\n",
       "  * easting                (easting) float32 -1542000.0 ... -1377000.0\n",
       "Data variables:\n",
       "    dw                     (time, northing, easting) float32 ...\n",
       "    ERODEDMASS             (time, northing, easting) float32 ...\n",
       "    ET                     (time, northing, easting) float32 ...\n",
       "    snd                    (time, northing, easting) float32 ...\n",
       "    rlds                   (time, northing, easting) float32 ...\n",
       "    rsds                   (time, northing, easting) float32 ...\n",
       "    MS_HNW                 (time, northing, easting) float32 ...\n",
       "    MS_SNOWPACK_RUNOFF     (time, northing, easting) float32 ...\n",
       "    MS_WIND                (time, northing, easting) float32 ...\n",
       "    pr                     (time, northing, easting) float32 ...\n",
       "    hur                    (time, northing, easting) float32 ...\n",
       "    snow_density           (time, northing, easting) float32 ...\n",
       "    SFC_SUBL               (time, northing, easting) float32 ...\n",
       "    SURF_ALB               (time, northing, easting) float32 ...\n",
       "    swe                    (time, northing, easting) float32 ...\n",
       "    ta                     (time, northing, easting) float32 ...\n",
       "    TOP_ALB                (time, northing, easting) float32 ...\n",
       "    TSG                    (time, northing, easting) float32 ...\n",
       "    ts                     (time, northing, easting) float32 ...\n",
       "    ws                     (time, northing, easting) float32 ...\n",
       "    VW_DRIFT               (time, northing, easting) float32 ...\n",
       "    WINDEROSIONDEPOSITION  (time, northing, easting) float32 ...\n",
       "Attributes:\n",
       "    date_created:              2020-10-29\n",
       "    creator_name:              erke2265\n",
       "    source:                    MeteoIO-2.90\n",
       "    history:                   2020-10-29T15:08:14Z, erke2265@shas0144.rc.int...\n",
       "    keywords_vocabulary:       AGU Index Terms\n",
       "    keywords:                  Cryosphere, Mass Balance, Energy Balance, Atmo...\n",
       "    title:                     Gridded data for various parameters and timesteps\n",
       "    institution:               colorado.edu\n",
       "    product_version:           1.0\n",
       "    Conventions:               CF-1.6,ACDD-1.3\n",
       "    standard_name_vocabulary:  CF-1.6\n",
       "    cdm_data_type:             Grid\n",
       "    geospatial_bounds_crs:     EPSG:3031\n",
       "    geospatial_bounds:         Polygon ((-1557000.0000000000 -125000.00000000..."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Open data sets as old (smaller domain) and new (larger domain)\n",
    "ds_new = xr.open_dataset(\"../output/grids/a3d_grids.nc\")\n",
    "ds_old = xr.open_dataset(\"../../a3d_grids.nc\")\n",
    "\n",
    "# Clip to common time\n",
    "n_time = len(ds_new['time'])\n",
    "ds_old =  ds_old.isel(time=slice(0, n_time))\n",
    "\n",
    "# Clip to common space\n",
    "ds_new = ds_new.isel(easting=slice(5, -5))\n",
    "ds_new = ds_new.isel(northing=slice(5, -5))\n",
    "\n",
    "ds_new"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Function to calculate delta SWE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_swe(ds):\n",
    "    dm = 1000 * (ds['swe'] - ds['swe'].isel(time=0))\n",
    "    swe_ts = dm.mean(dim='easting').mean(dim='northing')\n",
    "    swe_map = dm.isel(time=-1)\n",
    "    return swe_ts, swe_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compare SWE in clipped domain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SWE diff mean:\n",
      "5.4010086\n",
      "\n",
      "SWE Min:\n",
      "-176.45836\n",
      "\n",
      "SWE Mean:\n",
      "314.9076\n",
      "\n",
      "SWE Max:\n",
      "537.70825\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Delta SWE\n",
    "swe_new_ts, swe_new_map = calc_swe(ds_new)\n",
    "swe_old_ts, swe_old_map = calc_swe(ds_old)\n",
    "\n",
    "# Plot time series\n",
    "plt.figure(figsize=(15, 5))\n",
    "plt.plot(ds_new['time'], swe_new_ts, label='Larger Domain')\n",
    "plt.plot(ds_old['time'], swe_old_ts, label='Smaller Domain')\n",
    "plt.title(\"Mean SMB (mm w.e.) Caclulated Over the Same Domain\", fontsize=14)\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "\n",
    "# Plot time series difference\n",
    "plt.figure(figsize=(15, 5))\n",
    "plt.plot(ds_new['time'], swe_new_ts - swe_old_ts, label='Large - Small')\n",
    "plt.title(\"Mean SMB Difference (mm w.e.) Caclulated Over the Same Domain\", fontsize=14)\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "\n",
    "# Plot map of diff\n",
    "diff = swe_new_map - swe_old_map\n",
    "plt.figure(figsize=(30,15))\n",
    "plt.pcolor(diff, cmap=RdBu_11.mpl_colormap, vmin=-np.abs(diff).max(), vmax=np.abs(diff).max())\n",
    "plt.title(\"SMB Difference (mm w.e.): Larger - Smaller\", fontsize=14)\n",
    "plt.colorbar()\n",
    "\n",
    "# Plot map of SMB\n",
    "plt.figure(figsize=(30,15))\n",
    "plt.pcolor(swe_new_map, cmap=RdBu_11.mpl_colormap, vmin=-np.abs(swe_new_map).max(), vmax=np.abs(swe_new_map).max())\n",
    "plt.title(\"SMB (mm w.e.)\", fontsize=14)\n",
    "plt.colorbar()\n",
    "\n",
    "# Print min SMB\n",
    "print(\"SWE diff mean:\")\n",
    "print(diff.mean().values)\n",
    "print()\n",
    "\n",
    "print(\"SWE Min:\")\n",
    "print(swe_new_map.min().values)\n",
    "print()\n",
    "\n",
    "print(\"SWE Mean:\")\n",
    "print(swe_new_map.mean().values)\n",
    "print()\n",
    "\n",
    "print(\"SWE Max:\")\n",
    "print(swe_new_map.max().values)\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Close data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_new.close()\n",
    "ds_old.close()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "alpine3d",
   "language": "python",
   "name": "alpine3d"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
